Data analytics for mitigation of data center thermal issues

ABSTRACT

Mitigating the impact of data center thermal environmental issues on production applications includes retrieving, by a computer, from a centralized repository first data corresponding to I/O and processing activities of an infrastructure component executing one or more applications, second data corresponding to an application-to-infrastructure map, and third data corresponding to a business priority of the one or more applications. Based on the first data and the second data, the one or more applications are mapped to heat generation values of the infrastructure component, and based on the mapping a thermal load of the one or more applications on the infrastructure component is determined using data analytics. Using the third data, the computer identifies an execution priority for the one or more applications, generates a correlative mapping between the execution priority and the thermal load of the one or more applications, and generates a resolution plan based on the correlative mapping.

BACKGROUND

The present invention generally relates to the field of serviceinfrastructure, and more particularly to a computer implemented method,system, and computer program product for mitigating the impact of datacenter thermal environmental issues on production applications.

A data center (DC) is a facility used to house computer systems andassociated components, such as telecommunications and storage systems.Temperature in DC facilities naturally rises because the equipment inthe data center continuously converts electrical power to heat as abyproduct of performing work. Unless the heat is removed, the ambienttemperature increases, resulting in electronic equipment malfunction.Thus, the physical environment of a data center needs to be rigorouslycontrolled. For that purpose, cooling systems are typically used in theDC to control the air temperature and humidity level, such that ITinfrastructure components at the board level are kept withinmanufacturer's specified temperature and humidity ranges.

Typically, when a DC cooling system fails or abnormal thermal variancesoccur on the DC floor, non-critical applications are shut down to reduceheat dissipation and maintain DC thermal parameters under control. Thishelps in maintaining the availability of critical applications. If thesituation aggravates, further steps can be implemented for maintainingapplication availability including, for example, activating a disasterrecovery (DR) site and transfer workloads to an alternate facility.Unfortunately, these approaches do not align the resolution actions tobusiness events, cost imperatives, resiliency requirements, andapplication-related considerations. Thus, it would be desirable that analternate way to respond to thermal problems in a DC facility isavailable for interested parties.

SUMMARY

The present disclosure recognizes the shortcomings and problemsassociated with mitigation of thermal issues in a DC environment.Particularly, the need for a dynamic and real-time approach formitigating the impact of DC thermal problems based on a correlationbetween business events and application characteristics. Therefore,there is a need for a method and system to respond to DC thermalchallenges that include the resiliency of an application infrastructure,ongoing business events, execution priority, etc., and provide anapplication-oriented solution for maintaining availability of the ITinfrastructure and business applications.

Shortcomings of the prior art are overcome and additional advantages areprovided through the provision of a computer-implemented method formitigating an impact of thermal environmental issues in a data center.The method includes retrieving, by a computer, from a centralizedrepository first data corresponding to I/O and processing activities ofan infrastructure component executing one or more applications, seconddata corresponding to an application-to-infrastructure map, and thirddata corresponding to a business priority of the one or moreapplications. Based on the first data and the second data, the computermaps the one or more applications to heat generation values of theinfrastructure component, and based on the mapping determines a thermalload of the one or more applications on the infrastructure componentusing data analytics. Based on the third data, the computer identifiesan execution priority for the one or more applications and generates acorrelative mapping between the execution priority and the thermal loadof the one or more applications.

The method further includes retrieving, by the computer, from thecentralized repository fourth data corresponding to a plurality ofthermal parameters associated with the infrastructure component and aplurality of thermal parameters associated with the data center. Inresponse to determining that at least one parameter in the plurality ofthermal parameters associated with the infrastructure component and theplurality of thermal parameters associated with the data center exceedsa predefined threshold value, the computer generates a resolution planincluding an ordered sequence of resolution actions based on thecorrelative mapping between the execution priority and the thermal loadof the one or more applications.

Another embodiment of the present disclosure provides a computer programproduct for mitigating an impact of thermal environmental issues in adata center, according to the method described above.

Another embodiment of the present disclosure provides a computer systemfor mitigating an impact of thermal environmental issues in a datacenter, according to the method described above.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description, given by way of example and notintended to limit the invention solely thereto, will best be appreciatedin conjunction with the accompanying drawings, in which:

FIG. 1 is a block diagram illustrating a networked computer environment,according to an embodiment of the present disclosure;

FIG. 2A depicts a computer system for mitigating an impact of thermalenvironmental issues in a data center based on applicationprioritization, according to an embodiment of the present disclosure;

FIG. 2B depicts sample data pertaining to a point in time thermalenvironmental data associated with a data center, according to anembodiment of the present disclosure;

FIG. 3A depicts a flowchart illustrating the steps of acomputer-implemented method for correlating an application thermal loadto an execution priority, determined based on business needs, accordingto an embodiment of the present disclosure;

FIG. 3B depicts a flowchart illustrating the steps of acomputer-implemented method for generating a resolution plan foraddressing data center thermal problems using the correlative mappingbetween application thermal load and execution priority of FIG. 3A,according to an embodiment of the present disclosure;

FIG. 4 is a block diagram of internal and external components of acomputer system, according to an embodiment of the present disclosure;

FIG. 5 is a block diagram of an illustrative cloud computingenvironment, according to an embodiment of the present disclosure; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, according to an embodiment of thepresent disclosure.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention. In the drawings, like numbering representslike elements.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. This invention may, however, be embodied inmany different forms and should not be construed as limited to theexemplary embodiments set forth herein. In the description, details ofwell-known features and techniques may be omitted to avoid unnecessarilyobscuring the presented embodiments.

Indoor thermal environmental conditions in data centers (DC) can benegatively impacted by events such as failure of a coolinginfrastructure component, abnormal heat dissipation in DC computerequipment and the resulting formation of abnormal heat isles,inefficient cooling fluid flow, etc. Actions taken to resolve theseissues and control DC thermal environmental conditions may affectapplication availability, which in turn can impact business operationsand lead to tangible and intangible losses for clients and/orbusinesses. For instance, a development team may be working on a rapidrelease cycle to expedite the time-to-market of a product to gaincompetitive advantage. If a thermal event occurs in the DC during suchtime, there is no mechanism to factor in the business priority of suchapplications, and accordingly redefine the mitigation actions.

Instead, following traditional shutdown approaches can lead toavailability issues for the development system that can cause directrevenue impact to the business since traditional approaches forresponding to DC thermal environmental issues do not consider thecorrelation between business events and application characteristics.This in turn can translate into a critical application availabilityissue leading to a business productivity loss.

Accordingly, it would be desirable that solutions for DC thermal issuestake into account the business-related factors and correspondinglyadjust application priorities to determine the best course of action.For example, by analyzing application characteristics (e.g., applicationIO, processing rates, etc.), weighing their impact on the ITinfrastructure, and applying business/application priorities, amitigation plan can be developed for minimizing the impact of DC thermalenvironmental issues on business activities and goals.

Therefore, embodiments of the present invention provide a method,system, and computer program product for establishing a correlationbetween business events and application characteristics to generate aresolution plan that mitigates the impact of DC environmental thermalissues. The proposed embodiments can maintain resiliency of theapplication infrastructure and prevent potential disasters that canimpact critical applications. Particularly, the following describedexemplary embodiments provide a system, method, and computer programproduct to, among other things, determining a business priority of anapplication, mapping application IO and processing activity toinfrastructure heat generation, automatically performing a thermalimpact analysis of the applications on the IT infrastructure components,and applying the application priority information to the thermal impactanalysis for generating a resolution plan to mitigate the impact ofthermal environmental issues in a data center.

Thus, the present embodiments have the capacity to improve the technicalfield of service infrastructure by identifying computer systems that areat higher utilization (i.e., above average processing and IO activity),inter-system dependencies, and ongoing business events to perform acorrelative analysis based on which an optimal order of resolutionactions can be dynamically determined to reduce the impact of thermalenvironmental problems in an effective manner. The proposed embodimentscontinuously monitor applications at component level as well as the DCthermal parameters to dynamically assist clients on selecting the bestresolution actions during adverse thermal environmental situations.

Additionally, the proposed embodiments may, among other things, allowintelligent decision making to manage application availability during aDC thermal environmental issue, addressing the impact of DC thermalenvironmental issues with an application and business-priority-orientedview, generate analytics driven recommendations that enable IT managersto consider and implement multiple distinct options to manage theworkload availability during DC thermal environment issues, and developprediction models based on the estimated thermal impact on theapplication components to alert DC users.

Referring now to FIG. 1, an exemplary networked computer environment 100is depicted, according to an embodiment of the present disclosure. FIG.1 provides only an illustration of one embodiment and does not imply anylimitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironment may be made by those skilled in the art without departingfrom the scope of the invention, as recited by the claims.

The networked computer environment 100 may include a client computer 102and a communication network 110. The client computer 102 may include aprocessor 104, that is enabled to run a thermal issues impact mitigationprogram 108, and a data storage device 106. Client computer 102 may be,for example, a mobile device, a telephone (including smartphones), apersonal digital assistant, a netbook, a laptop computer, a tabletcomputer, a desktop computer, or any type of computing devices capableof accessing a network.

The networked computer environment 100 may also include a servercomputer 114 with a processor 118, that is enabled to run a softwareprogram 112, and a data storage device 120. In some embodiments, servercomputer 114 may be a resource management server, a web server or anyother electronic device capable of receiving and sending data. Inanother embodiment, server computer 114 may represent a server computingsystem utilizing multiple computers as a server system, such as in acloud computing environment.

The thermal issues impact mitigation program 108 running on clientcomputer 102 may communicate with the software program 112 running onserver computer 114 via the communication network 110. As will bediscussed with reference to FIG. 4, client computer 102 and servercomputer 114 may include internal components and external components.

The networked computer environment 100 may include a plurality of clientcomputers 102 and server computers 114, only one of which is shown. Thecommunication network 110 may include various types of communicationnetworks, such as a local area network (LAN), a wide area network (WAN),such as the Internet, the public switched telephone network (PSTN), acellular or mobile data network (e.g., wireless Internet provided by athird or fourth generation of mobile phone mobile communication), aprivate branch exchange (PBX), any combination thereof, or anycombination of connections and protocols that will supportcommunications between client computer 102 and server computer 114, inaccordance with embodiments of the present disclosure. The communicationnetwork 110 may include wired, wireless or fiber optic connections. Asknown by those skilled in the art, the networked computer environment100 may include additional computing devices, servers or other devicesnot shown.

Plural instances may be provided for components, operations, orstructures described herein as a single instance. Boundaries betweenvarious components, operations, and data stores are somewhat arbitrary,and particular operations are illustrated in the context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within the scope of the present invention. Ingeneral, structures and functionality presented as separate componentsin the exemplary configurations may be implemented as a combinedstructure or component. Similarly, structures and functionalitypresented as a single component may be implemented as separatecomponents. These and other variations, modifications, additions, andimprovements may fall within the scope of the present invention.

Referring now to FIGS. 2A-2B, a computer system 200 for mitigating theimpact of data center thermal issues in a data center is shown,according to an embodiment of the present disclosure.

According to an embodiment, the computer system 200 via, for example,the thermal issues impact mitigation program 108 (FIG. 1) collects aplurality of data corresponding to a processing load and thermalenvironmental parameters associated with the data center facility and ITinfrastructure components as well as the individual thresholds of ITinfrastructure components. The plurality of data collected by thecomputer system 200 can be retrieved from, for example, data centerinfrastructure management (DCIM) tools or other existing informationrepositories (e.g., Enterprise Data Lake). As known by those skilled inthe art, DCIM tools monitor, measure, manage and/or control data centerutilization and energy consumption of all IT-related equipment (such asservers, storage, and network switches) and facility infrastructurecomponents (such as power distribution units [PDUs] and computer roomair conditioners [CRACs]). DCIM tools also poll and gather environmentaldata within the DC from sensors and monitoring equipment.

According to an embodiment, the computer system 200 automaticallycollects data associated with a processing load of all applicationsbeing executed by the computer system 200 Specifically, as illustratedin the figure, the computer system 200 collects data associated with I/Oand processing activity of all application components at 202, dataassociated with application to infrastructure maps at 204 (i.e.,identifying and mapping interactions and relationships betweenapplications and the underlying infrastructure), and data associatedwith IT infrastructure to DC physical floor tile maps, real-time coolingflows, and physical space cooling characteristics (e.g., coolingcharacteristics of physical racks at various heights) at 206. As knownby those skilled in the art, all IT infrastructure components consumepower in order to operate, and power produces heat. Thus, applicationswith high processing loads can be recognized as producing or dissipatinghigher amounts of heat.

Simultaneous to obtaining processing load information, the computersystem 200 collects thermal data associated with the DC environment(e.g., environmental parameters) and IT infrastructure components. Forexample, the computer system 200 collects data associated with thermalparameters and thresholds of all infrastructure components at 208 (i.e.,manufacturer's settings, normal operating range of ambient temperatures,current operating temperature values, etc.), and data associated withreal-time environmental parameters from instruments and sensors in theDC and DC tile thresholds at 210 (e.g., temperature, humidity, etc.).According to an embodiment, instruments and sensors from which real-timeenvironmental parameters can be retrieved may include internet-of-things(IoT) devices present in the DC facility. Thermal data collected fromavailable IT infrastructure components and IoT sensors can then becompared with identified thresholds values associated with ITinfrastructure and DC components and environmental parameters (e.g.,maximum operating temperature range for infrastructure components vs.current DC temperature).

Further, in this embodiment, the computer system 200 collectsinformation corresponding to ongoing business events and schedules at212. By doing this, the computer system 200 can determine an executionpriority for each application at a determined time and categorizeapplications based on a business priority. Stated differently, thecomputer system 200 can determine which applications are the mostimportant from a business perspective and recommend an order in whichthey need to be executed for an effective business operation.

In some embodiments, the plurality of data collected by the computersystem 200 at 202, 204, 206, 208, and 210 can be stored in a centralizedrepository (not shown) associated with the data center facility.

According to an embodiment, the computer system 200 performs at 214 ananalysis of the collected I/O and processing activity (202) andapplication to infrastructure maps (204) using correlative analytics toassess the thermal impact of each application on infrastructurecomponents. Specifically, the computer system 200 via an analyticsengine, generates at 214 a correlative mapping of the application's I/Oactivities to heat generation of one or more infrastructure componentsbased on which a thermal impact analysis of the application can beperformed. Based on the thermal impact analysis, the computer system 200may determine a behavior of the one or more infrastructure componentswhen thermal problems occur and there are overall changes in operatingconditions.

As the correlative analytics assessment is performed, the computersystem 200 determines threshold breaches in thermal parameter(s)associated with one or more DC environmental conditions andinfrastructure components. Accordingly, the computer system 200determines at 218, based on the real-time sensor environmental data(210), whether a thermal parameter associated with the DC has exceeded apredefined threshold. Similarly, the computer system 200 determines at216, based on the collected thermal data for each infrastructurecomponent (208), whether a thermal threshold or thermal parameterassociated with one or more infrastructure components exceeds apredefined value. If the computer system 200 determines at 216 and 218that thermal values associated with the DC environment andinfrastructure components are within a normal range, the computer system200 stops the verification process.

In response to determining at 216 and 218 that at least one of a DCthermal environmental threshold and an infrastructure component thermalthreshold have been exceeded, the computer system 200 at 220 validatesand reconciles the thermal impact analysis performed at 214 with theinfrastructure components mapping collected at 206 and infrastructurecomponent and DC thermal threshold breaches detected at 216, 218. Datacollected at 206 may include infrastructure to DC physical floor tilemaps, real-time cooling flows, and physical space coolingcharacteristics.

It should be note that the validation of the thermal impact analysisperformed at 220 represents a critical safety check for the wholecomputer system 200. Specifically, if at 220 the data collected at 202,204 (left branch of the computer system 200) does not correlate with thedata collected at 206, 208, 210 (right branch of the computer system200), it indicates that the collected data is out of sync and there arepossible gaps on either branch of the computer system 200 that arecausing such a discrepancy which must be addressed. When both sidesreconcile with each other (i.e., collected data correlates) at 220, itis an evidence that all data collected is in order and actionable, andthe computer system 200 continues with the next action.

According to an embodiment, the computer system 200 then adds to thethermal impact analysis, at 222, the application priority informationdetermined using the business events and schedules data collected at212. Specifically, the computer system 200 at 222 maps applicationprioritization to thermal impact analysis information performed at 220such that, in the event of a thermal problem, applications with a highbusiness priority are kept available.

Accordingly, the computer system 200 dynamically analyzes businessconsiderations and determines relative prioritization of applicationsbased on the application thermal impact analysis (220) and applicationpriority information (222). In some embodiments, the computer system 200may allow stakeholders or investors to tag application priorities in asystem readable configuration file and dynamically factor in suchinputs. Thus, the computer system 200 can maintain a dynamic applicationexecution priority list including an order of preference determinedaccording to business needs and application characteristics thatguarantees availability of high priority applications when the DCthermal issues occur.

Based on the application thermal impact analysis and applicationpriority information, the computer system 200 generates at 224 aresolution plan for addressing the impact of a current thermalenvironmental issue including distributing at 226 the resolution plan tointerested parties (e.g., corresponding IT managers, businessstakeholders, investors, etc.). According to an embodiment, thegenerated resolution plan may recommend or suggest performing thefollowing actions:

1) Identify applications or application components that can be shutdownsafely;

2) Identify applications or application components that can be failedover or transparently migrated to other infrastructure componentsresiding in the same DC or site;

3) Identify applications that can be failed over to an alternate site;

4) Identify applications or application components that may need to bescaled down or distributed to other computer equipment without impactingavailability;

5) Redirect a processing load by reconfiguring load balancers;

6) Re-adjust and redistribute DC cooling flows based on anticipatedthermal indices in heat isles of the DC; and

7) Share the resolution plan with interested parties for follow-upactions.

Data center, infrastructure and application (DC/Infra/App) teams mayfurther develop specific actions plans in-line with the recommendationsin the resolution plan (224) to address an ongoing DC environmentalissue while maintaining the availability of applications that holdhighest priority at a current time. Additionally, the computer system200 can analyze time series thermal data of applications and establish athermal prediction model. This data can be utilized to proactivelypredict the thermal impact on the application components and notify ITmanagers, so they are prepared in advance to handle adverse situationseffectively. More particularly, the thermal prediction model can begenerated using machine learning (ML) and artificial intelligence (AI).Since the computer system 200 maintains historic data of previousoccurrences of DC thermal events and the actions taken thereof, the MLcomponent learns from interpreting the historic data and predicts futureevents when associated base conditions begin to develop in the DC.

With reference now to FIG. 2B, a table 250 shows an illustration of DCenvironmental data collected, correlated and reconciled when a DCthermal issue has occurred. Specifically, table 250 shows the thresholdsbreached, the floor space where it occurred, the infrastructure racks onthe floor where breaches have occurred and the IT systems involved inthe threshold breaches.

In this exemplary embodiment, a client (e.g., company X) has two datacenters (DC): Primary Data Center (DC_A) and Secondary Data Center(DC_B). All client business applications (e.g., Prod, Dev, Test etc.)and associated infrastructure are hosted in DC_A, while DC_B is adisaster recovery (DR) facility. Local high availability is configuredat the storage layer in DC_A.

According to an embodiment, applications and associated infrastructureare hosted in DC_A according to the following outline:

1) Production application (App_A) constitutes two virtual machines(VMs), i.e., VM_A and VM_B, and the corresponding storage is served fromprimary and secondary storage systems STG_A, STG_B, respectively. Theprimary and secondary storage systems STG_A, STG_B are configured inhighly available (HA) topology.

2) Development (Dev) application (App_B) constitutes two VMs, i.e., VM_Cand VM_D, and the corresponding storage is served from storage systemSTG_A.

3) Test application (App_C) constitutes two VMs, i.e., VM_E and VM_F,and the storage is served from storage system STG_A.

4) Network infrastructure associated with all these applications isinstalled in rack A located in DC_A floor tile 05.

5) Computer systems associated with App_A, App_B and App_C are installedin rack B, at various heights located in DC_A floor tile 10.

6) Primary Storage system STG_A serving App_A, App_B and App_C isinstalled in rack C, located in DC_A floor tile 15.

7) Secondary Storage system STG_B serving App_A, App_B and App_C isinstalled in rack D, located in DC_A floor tile 20.

Similarly, in this embodiment, cooling areas in DC_A are organizedaccording to the following outline:

1) Precision Air Conditioning Unit (PACU)1 is serving components hostedin rack A.

2) PACU2 is serving components hosted in rack B.

3) PACU3 is serving components hosted in rack C.

4) PACU4 is serving components hosted in rack D.

For illustration purposes, it is assumed that a cooling component in theDC has failed, and that the thermal parameter readings (e.g.,temperature) associated with the storage systems are gradually rising(based on heat dissipation in the hardware components). As explainedabove, a situation like this can cause, for example, an automaticshutdown of the storage subsystems and resulting application outages, ora failure of storage subsystems, if the thermal environmental issuepersists for an extended amount of time. Thus, to maintain availabilityof critical applications, the proposed computer system 200 formitigating the impact of thermal issues in a data center based on anapplication priority performs the following steps:

1) Perform an application thermal impact analysis by:

a) collecting metrics associated with real-time I/O and processingactivity 202 (FIG. 2A) from all the application components and thermalparameters of each hardware subsystem, i.e., computer, storage andnetwork.

b) using the application-to-infrastructure mapping 204 (FIG. 2A), a loadanalysis is performed to determine a relative impact of I/O andprocessing activity on the source (e.g., computer) and target (e.g.,storage, network) infrastructure components. According to the presentexemplary embodiment, based on the load analysis the computer system 200determines that: VM_C is the top contributor of thermal dissipation onsource and target infrastructure components due to the load running onit; VM_A and VM_B are the next top contributors of thermal dissipationon source and target infrastructure components; and VM_F is the leastcontributor of thermal dissipation on source and target infrastructurecomponents.

2) All DC environmental data including cooling flow data and DCheatmaps, and infrastructure component temperatures are collected inreal-time (206, 208, 210).

3) Information on business metrics, business and application priorities,business events and schedules etc. is collected and maintained in acentralized repository (212). As mentioned above, in some embodiments,stakeholders can review and provide an input on application priority.Based on the collected business-related information, the computer system200 determines that: App_B is currently critical to the client as itsexternal launch and go to market dates are rapidly approaching (thisproduct release cycle dictates priority); App_A is critical as aproduction application (current top revenue earner); and App_C is anon-critical application.

Assuming that the failed cooling component is PACU3 in DC_A, PACU3failure can lead to inefficient cooling near rack C where the primarystorage system STG_A is located, as indicated by the shaded rows inTable 250. Accordingly, the computer system 200 polls and monitorsthermal parameters corresponding to the storage systems. When thethermal readings exceed the predefined thermal thresholds, automaticallya storage system threshold deviation flag is generated based on theapplication thermal impact analysis.

4) Based on the business and application priorities, an overallmitigation plan is proposed to the stakeholders as a sequence ofmitigation steps in an optimal order (224, 226). For instance, apossible sequence of mitigation steps may include, but are not limitedto:

a) Migrate VM_C data store from STG_A to STG_B;

b) Redirect the I0 from VM_A and VM_B to STG_B (secondary volumes) andmark the primary volumes offline;

c) Monitor the thermal parameters of the storage system STG_A;

d) If the temperature does not fall below threshold, shutdown VM_F; and

e) If the DC thermal cooling failure issue still persists, propose nextset of actions including, for example, failing over critical workloadsto the DR facility.

It should be noted that, the example sequence of mitigation stepsproposed above takes into account the most critical workloads as well asbusiness priorities at a present time, as opposed to static,predetermined action plans for shutting down workloads during thermalevents that neglect the impact of application shutdown on businessactivities.

Referring now to FIG. 3A, a flowchart 300 illustrating the steps of acomputer-implemented method for correlating an application thermal loadto an execution priority based on business needs is shown, according toan embodiment of the present disclosure.

The process starts at 302 by retrieving from a centralized repositoryfirst data corresponding to I/O and processing activities ofinfrastructure components executing one or more applications, seconddata corresponding to application-to-infrastructure maps, and third datacorresponding to a business priority of the one or more applications. Atstep 304, based on the retrieved first data and second data, one or moreapplications are mapped to heat generation values of correspondinginfrastructure components.

The process continues at step 306 in which, based on the mapping of theone or more applications to heat generation values of the infrastructurecomponents, a thermal load of the one or more applications on theinfrastructure components can be determined using data analytics. Atstep, 308 an execution priority associated with the one or moreapplications is identified based on the retrieved third data. The thirddata may include, for example, information corresponding to businessmetrics, business and application priorities, business events andschedules from which an execution priority for the one or moreapplications can be determined.

Finally, a correlative mapping between the determined execution priorityand the thermal load of the one or more applications is generated atstep 310. It should be noted that data corresponding to infrastructureto data center tile maps, real-time cooling flows, and physical spacecooling characteristics can also be retrieved from the centralizedrepository and added to the correlative mapping between the executionpriority and the thermal load of the one or more applications. As willbe described in detail below with reference to FIG. 3B, the generatedcorrelative mapping can be used to create a resolution plan foraddressing the impact of thermal problems in the data center focused onmaintaining the availability of high priority applications.

Referring now to FIG. 3B, a flowchart 320 illustrating the steps of acomputer-implemented method for generating a resolution plan foraddressing the impact of thermal problems using the correlative mappingbetween application thermal load and execution priority of FIG. 3A isshown, according to an embodiment of the present disclosure.

In this embodiment, the process starts at step 322 by retrieving fromthe centralized repository fourth data corresponding to a plurality ofthermal parameters associated with the infrastructure components and aplurality of thermal parameters associated with the data center.Specifically, the fourth data corresponding to thermal parameters of theinfrastructure components and thermal parameters of the data centerincludes thermal thresholds and parameters associated with eachinfrastructure component and real-time environmental data from the datacenter and data center tiles. According to an embodiment, the real-timeenvironmental data from the data center and data center tiles can beobtained from a plurality of internet of things devices available withinthe data center facility.

At step 324, it is determined whether at least one parameter in theplurality of thermal parameters associated with the infrastructurecomponents and the plurality of thermal parameters associated with thedata center exceeds a predefined threshold value. In response todetermining, at step 326, that the at least one parameter in theplurality of thermal parameters associated with the infrastructurecomponents and the plurality of thermal parameters associated with thedata center exceeded the predefined threshold value, an ordered sequenceof resolution actions based on the correlative mapping between theexecution priority and the thermal load of the one or more applicationsis generated at step 328. If, at step 326, it is determined that none ofthe plurality of thermal parameters associated with the infrastructurecomponents and the plurality of thermal parameters associated with thedata center exceeds the predefined threshold value, the process returnsto step 322 to continue monitoring the plurality of thermal parameters.

The process continues at step 330 in which the resolution plan isexecuted for controlling at least one parameter exceeding the predefinedthreshold value while maintaining availability of high priorityapplications.

According to an embodiment, the ordered sequence of resolution actionsbased on the correlative mapping between the execution priority and thethermal load of one or more applications may include the followingsteps: identify at least one application from the one or moreapplications that can be shutdown safely, identify at least oneapplication from the one or more applications that can be failed over toother infrastructure components within the data center, identify atleast one application from the one or more applications that can befailed over to an alternate site, identify at least one application fromthe one or more applications that can be distributed to other computerequipment without impacting application availability, redirect aprocessing load by reconfiguring load balancers, and readjust andredistribute cooling flows within the data center based, at least inpart, on anticipated thermal indices in heat isles of the data center.Further, the resolution plan can be automatically distributed betweendata center managers.

In some embodiments, data center managers and business stakeholders arecapable of providing inputs. The latter can also assign and modify theapplication priorities which can be used to update data related toapplication priorities. This can be accomplished by a system readableconfiguration file in the thermal impact issues mitigation program. Allsuch inputs are factored dynamically in the mitigation plan generation.

Therefore, embodiments of the present disclosure provide a method andsystem for addressing the impact of thermal environmental issues in adata center that maintain application availability based onbusiness-related considerations as well as application characteristics,as opposed to an infrastructure-oriented view. The proposed embodimentsmay minimize revenue losses from incidents related to environmentalthermal issues. Application of the proposed embodiments at, for example,cloud data centers and managed service facilities may help companiesminimizing adverse business impact to its clients when problems relatedto DC thermal environmental issues occur.

The proposed embodiments provide a resolution plan based on acorrelation between business events and application characteristics thatprioritizes maintaining the resiliency of an application infrastructure.During an adverse thermal environmental event, the proposed embodimentsare capable of aligning resolution actions to ongoing business eventsand accordingly prioritize application execution for minimizing theimpact of the thermal event on the overall business. The proposedembodiments take into account that external events, business priorities,rapid application release cycles, time to market considerations, andnewer operational models cause the business priorities to varydynamically, and thus the applications hold varying degrees ofimportance cyclically from a business point of view.

Referring now to FIG. 4, a block diagram of components of clientcomputer 102 and server computer 114 of networked computer environment100 of FIG. 1 is shown, according to an embodiment of the presentdisclosure. It should be appreciated that FIG. 4 provides only anillustration of one implementation and does not imply any limitationsregarding the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be made.

Client computer 102 and server computer 114 may include one or moreprocessors 402, one or more computer-readable RAMs 404, one or morecomputer-readable ROMs 406, one or more computer readable storage media408, device drivers 412, read/write drive or interface 414, networkadapter or interface 416, all interconnected over a communicationsfabric 418. Communications fabric 418 may be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system.

One or more operating systems 410, and one or more application programs411 are stored on one or more of the computer readable storage media 408for execution by one or more of the processors 402 via one or more ofthe respective RAMs 404 (which typically include cache memory). In theillustrated embodiment, each of the computer readable storage media 408may be a magnetic disk storage device of an internal hard drive, CD-ROM,DVD, memory stick, magnetic tape, magnetic disk, optical disk, asemiconductor storage device such as RAM, ROM, EPROM, flash memory orany other computer-readable tangible storage device that can store acomputer program and digital information.

Client computer 102 and server computer 114 may also include a R/W driveor interface 414 to read from and write to one or more portable computerreadable storage media 426. Application programs 411 on client computer102 and server computer 114 may be stored on one or more of the portablecomputer readable storage media 426, read via the respective R/W driveor interface 414 and loaded into the respective computer readablestorage media 408.

Client computer 102 and server computer 114 may also include a networkadapter or interface 416, such as a TCP/IP adapter card or wirelesscommunication adapter (such as a 4G wireless communication adapter usingOFDMA technology) for connection to a network 428. Application programs411 on client computer 102 and server computer 114 may be downloaded tothe computing device from an external computer or external storagedevice via a network (for example, the Internet, a local area network orother wide area network or wireless network) and network adapter orinterface 416. From the network adapter or interface 416, the programsmay be loaded onto computer readable storage media 408. The network maycomprise copper wires, optical fibers, wireless transmission, routers,firewalls, switches, gateway computers and/or edge servers.

Client computer 102 and server computer 114 may also include a displayscreen 420, a keyboard or keypad 422, and a computer mouse or touchpad424. Device drivers 412 interface to display screen 420 for imaging, tokeyboard or keypad 422, to computer mouse or touchpad 424, and/or todisplay screen 420 for pressure sensing of alphanumeric character entryand user selections. The device drivers 412, R/W drive or interface 414and network adapter or interface 416 may include hardware and software(stored on computer readable storage media 408 and/or ROM 406).

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 5, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 5 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 6, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and system for mitigation of data centerthermal issues 96.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While steps of the disclosed method and components of the disclosedsystems and environments have been sequentially or serially identifiedusing numbers and letters, such numbering or lettering is not anindication that such steps must be performed in the order recited, andis merely provided to facilitate clear referencing of the method'ssteps. Furthermore, steps of the method may be performed in parallel toperform their described functionality.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method for mitigating animpact of thermal issues in a data center, comprising: retrieving, by acomputer, from a centralized repository first data corresponding to I/Oand processing activities of an infrastructure component executing oneor more applications, second data corresponding to anapplication-to-infrastructure map, and third data corresponding to abusiness priority of the one or more applications; based on the firstdata and the second data, mapping, by the computer, the one or moreapplications to heat generation values of the infrastructure component;based on the mapping, determining, by the computer, a thermal load ofthe one or more applications on the infrastructure component using dataanalytics; based on the third data, identifying, by the computer, anexecution priority for the one or more applications; and generating, bythe computer, a correlative mapping between the execution priority andthe thermal load of the one or more applications.
 2. The method of claim1, further comprising; retrieving, by the computer, from the centralizedrepository fourth data corresponding to a plurality of thermalparameters associated with the infrastructure component and a pluralityof thermal parameters associated with the data center; and in responseto determining that at least one parameter in the plurality of thermalparameters associated with the infrastructure component and theplurality of thermal parameters associated with the data center exceedsa predefined threshold value, generating, by the computer, a resolutionplan comprising an ordered sequence of resolution actions based on thecorrelative mapping between the execution priority and the thermal loadof the one or more applications.
 3. The method of claim 2, furthercomprising; executing, by the computer, the resolution plan forcontrolling the at least one parameter exceeding the predefinedthreshold value.
 4. The method of claim 1, further comprising:retrieving from the centralized repository, by the computer, fifth datacorresponding to, at least in part, infrastructure to data center tilemaps, real-time cooling flows, and physical space coolingcharacteristics; and adding, by the computer, the fifth data to thecorrelative mapping between the execution priority and the thermal loadof the one or more applications.
 5. The method of claim 1, wherein thethird data corresponding to a business priority of the one or moreapplications comprises information corresponding to at least one ofbusiness metrics, business and application priorities, business events,and schedules.
 6. The method of claim 2, wherein the fourth datacorresponding to the thermal parameters of the infrastructure componentand the thermal parameters of the data center comprises thermalthresholds and parameters associated with the infrastructure component,and real-time environmental data from the data center and data centertiles.
 7. The method of claim 6, wherein the real-time environmentaldata from the data center and the data center tiles is obtained from aplurality of internet of things devices.
 8. The method of claim 2,wherein the ordered sequence of resolution actions based on thecorrelative mapping between the execution priority and the thermal loadof the one or more applications further comprises executing at least oneof the following steps: identifying, by the computer, at least oneapplication from the one or more applications that can be shutdownsafely; identifying, by the computer, at least one application from theone or more applications that can be failed over to other infrastructurecomponents within the data center; identifying, by the computer, atleast one application from the one or more applications that can befailed over to an alternate site; identifying, by the computer, at leastone application from the one or more applications that can bedistributed to other computer equipment without impacting applicationavailability; redirecting, by the computer, a processing load byreconfiguring load balancers; and readjusting and redistributing, by thecomputer, cooling flows within the data center based, at least in part,on anticipated thermal indices in heat isles of the data center.
 9. Themethod of claim 2, further comprising; distributing, by the computer,the resolution plan between data interested parties; and receiving, bythe computer, an input from the interested parties for executing theresolution plan including an updated execution priority for the one ormore applications.
 10. A computer system for mitigating an impact ofthermal issues in a data center, comprising: one or more processors, oneor more computer-readable memories, one or more computer-readabletangible storage devices, and program instructions stored on at leastone of the one or more storage devices for execution by at least one ofthe one or more processors via at least one of the one or more memories,wherein the computer system is capable of performing a methodcomprising: retrieving, by a computer, from a centralized repositoryfirst data corresponding to I/O and processing activities of aninfrastructure component executing one or more applications, second datacorresponding to an application-to-infrastructure map, and third datacorresponding to a business priority of the one or more applications;based on the first data and the second data, mapping, by the computer,the one or more applications to heat generation values of theinfrastructure component; based on the mapping, determining, by thecomputer, a thermal load of the one or more applications on theinfrastructure component using data analytics; based on the third data,identifying, by the computer, an execution priority for the one or moreapplications; and generating, by the computer, a correlative mappingbetween the execution priority and the thermal load of the one or moreapplications.
 11. The computer system of claim 10, further comprising;retrieving, by the computer, from the centralized repository fourth datacorresponding to a plurality of thermal parameters associated with theinfrastructure component and a plurality of thermal parametersassociated with the data center; and in response to determining that atleast one parameter in the plurality of thermal parameters associatedwith the infrastructure component and the plurality of thermalparameters associated with the data center exceeds a predefinedthreshold value, generating, by the computer, a resolution plancomprising an ordered sequence of resolution actions based on thecorrelative mapping between the execution priority and the thermal loadof the one or more applications.
 12. The computer system of claim 11,further comprising; executing, by the computer, the resolution plan forcontrolling the at least one parameter exceeding the predefinedthreshold value.
 13. The computer system of claim 10, furthercomprising: retrieving from the centralized repository, by the computer,fifth data corresponding to, at least in part, infrastructure to datacenter tile maps, real-time cooling flows, and physical space coolingcharacteristics; and adding, by the computer, the fifth data to thecorrelative mapping between the execution priority and the thermal loadof the one or more applications.
 14. The computer system of claim 10,wherein the third data corresponding to a business priority of the oneor more applications comprises information corresponding to at least oneof business metrics, business and application priorities, businessevents, and schedules.
 15. The computer system of claim 11, wherein thefourth data corresponding to the thermal parameters of theinfrastructure component and the thermal parameters of the data centercomprises thermal thresholds and parameters associated with theinfrastructure component, and real-time environmental data from the datacenter and data center tiles.
 16. The computer system of claim 15,wherein the real-time environmental data from the data center and thedata center tiles is obtained from a plurality of internet of thingsdevices.
 17. The computer system of claim 11, wherein the orderedsequence of resolution actions based on the correlative mapping betweenthe execution priority and the thermal load of the one or moreapplications further comprises executing at least one of the followingsteps: identifying, by the computer, at least one application from theone or more applications that can be shutdown safely; identifying, bythe computer, at least one application from the one or more applicationsthat can be failed over to other infrastructure components within thedata center; identifying, by the computer, at least one application fromthe one or more applications that can be failed over to an alternatesite; identifying, by the computer, at least one application from theone or more applications that can be distributed to other computerequipment without impacting application availability; redirecting, bythe computer, a processing load by reconfiguring load balancers; andreadjusting and redistributing, by the computer, cooling flows withinthe data center based, at least in part, on anticipated thermal indicesin heat isles of the data center.
 18. The computer system of claim 11,further comprising; distributing, by the computer, the resolution planbetween data interested parties; and receiving, by the computer, aninput from the interested parties for executing the resolution planincluding an updated execution priority for the one or moreapplications.
 19. A computer program product for mitigating an impact ofthermal issues in a data center, comprising: one or more computerreadable storage media, and program instructions collectively stored onthe one or more computer readable storage media, the programinstructions comprising: program instructions to retrieve, by acomputer, from a centralized repository first data corresponding to I/Oand processing activities of an infrastructure component executing oneor more applications, second data corresponding to anapplication-to-infrastructure map, and third data corresponding to abusiness priority of the one or more applications; based on the firstdata and the second data, program instructions to map, by the computer,the one or more applications to heat generation values of theinfrastructure component; based on the mapping, program instructions todetermine, by the computer, a thermal load of the one or moreapplications on the infrastructure component using data analytics; basedon the third data, program instructions to identify, by the computer, anexecution priority for the one or more applications; and programinstructions to generate, by the computer, a correlative mapping betweenthe execution priority and the thermal load of the one or moreapplications.
 20. The computer program product of claim 19, furthercomprising; program instructions to retrieve, by the computer, from thecentralized repository fourth data corresponding to a plurality ofthermal parameters associated with the infrastructure component and aplurality of thermal parameters associated with the data center; inresponse to determining that at least one parameter in the plurality ofthermal parameters associated with the infrastructure component and theplurality of thermal parameters associated with the data center exceedsa predefined threshold value, program instructions to generate, by thecomputer, a resolution plan comprising an ordered sequence of resolutionactions based on the correlative mapping between the execution priorityand the thermal load of the one or more applications; and programinstructions to execute, by the computer, the resolution plan forcontrolling the at least one parameter exceeding the predefinedthreshold value.